cpda: Probability Density Approximation
In TasCL/cpda: Probability Density Approximation

Description Author(s) References

Uses Silverman's (1982) KDE-FFT method to fit probability densities. This package implements fast truncated-Gaussian, ex-Gaussian, inverse-Gaussian distributions via GNU scientific library in Boost C++ libraries.

Yi-Shin Lin <yishin.lin@utas.edu.au>, Andrew Heathcote <andrew.heathcote@utas.edu.au>, & William Holmes <william.holmes@vanderbilt.edu>

Cousineau, D., Brown, S. & Heathcote, A. (2004). Fitting distributions using maximum likelihood: Methods and packages. Behavior Research Methods, Instruments, & Computers 36(4), 742-756. https://doi.org/10.3758/BF03206555.

Holmes, W. (2015). A practical guide to the Probability Density Approximation with improved implementation and error characterization. Journal of Mathematical Psychology, 68-69, 13–24. https://doi.org/10.1016/j.jmp.2015.08.006.

Michael, J., Schucany, W., & Haas, R. (1976). Generating Random Variates Using Transformations with Multiple Roots. The American Statistician, 30(2), 88-90. https://doi:10.2307/2683801

Wheeler, B (2009). SuppDists: Supplementary Distributions. R package version 1.1-9.4. https://CRAN.R-project.org/package=SuppDists.

Stasinopoulos, M. & Rigby, B. (2016). gamlss.dist: Distributions to be Used for GAMLSS Modelling. R package version 5.0-0. https://CRAN.R-project.org/package=gamlss.dist

TasCL/cpda documentation built on May 3, 2019, 11:48 p.m.